Total 56,830 skills, AI & Machine Learning has 9448 skills
Showing 12 of 9448 skills
Implementation planning skill. Creates detailed technical plans through interactive research and iteration.
Connect to SageMaker Managed MLflow (mlflow-app or mlflow-tracking-server ARN) as an MLflow backend, then hand off to the other MLflow skills. Triggers on a SageMaker MLflow ARN (arn:aws:sagemaker:...:mlflow-app/... or arn:aws:sagemaker:...:mlflow-tracking-server/...) or "SageMaker Managed MLflow".
Iteratively inspect traces, interview the user, and create LangSmith online evaluators one at a time. Use specifically for creating online evaluators for use within LangSmith -- use "eval-engineering" for Harbor-style online evaluations.
Answer a question across a corpus of contract documents with verified citations. Use when the user asks what a contract says, which contracts have a clause, what changed between amendments, or any question that needs reading and citing across a set of contract files. The corpus must be on the local filesystem (see README).
Route any dropped-in input — idea, spec path, file path, PR or issue, stack trace, bug report, or bare `/cheese` — to the right workflow skill. Use as the unified entry point — phrases include "/cheese", "what should I do with this", "help me get started", "route this", or any opening message that does not already name a downstream skill.
Evidence-grounded legacy-repository understanding with recurrent human feedback and bounded skill convergence. Activates when the user asks to understand, map, document, onboard to, refactor, modify, or assess a repository.
Guide for creating, structuring, and improving Claude skills (SKILL.md). Use when building a new skill, reviewing an existing skill, writing SKILL.md frontmatter, defining trigger conditions, troubleshooting skill problems (not triggering, over-triggering, instructions not followed), or planning skill distribution. When working on any skill in this repository: also load the cc-best-practices skill, and always update both CLAUDE.md and README.md skill tables after any skill change. Do NOT use for general Claude Code configuration or hook setup.
Validate and use CPU offloading in Megatron Bridge, including layer-level activation offloading and fractional optimizer state offloading with HybridDeviceOptimizer.
Query and browse evaluation results stored in MLflow. Use when the user wants to look up runs by invocation ID, compare metrics across models, fetch artifacts (configs, logs, results), or set up the MLflow MCP server. ALWAYS triggers on mentions of MLflow, experiment results, run comparison, invocation IDs in the context of results, or MLflow MCP setup.
Create and manage agent graphs — directed graphs of configs connected by edges with handoff logic. Use when building multi-agent workflows where configs route to each other.
Give your AI agents capabilities through tools (function calling). Helps you identify what your AI needs to do, create tool definitions, and attach them to AI Config variations.
cuOpt REST server — what it does and how requests flow. Domain concepts; no deploy or client code.